}
  absl::Status SetAttrFunctionName(const char* attr_name, const char* value,
                                   size_t length) override {
    tensorflow::NameAttrList func_name;
    func_name.set_name(string(value, value + length));
    op_->node_builder.Attr(attr_name, func_name);
    return absl::OkStatus();
  }
  absl::Status SetAttrTensor(const char* attr_name,
                             AbstractTensorInterface* tensor) override {

  delete lib_handle;
}

void TF_GraphRemoveFunction(TF_Graph* g, const char* func_name,
                            TF_Status* status) {
  tensorflow::mutex_lock l(g->mu);
  status->status = g->graph.mutable_flib_def()->RemoveFunction(func_name);

}

void TF_SetAttrFuncName(TF_OperationDescription* desc, const char* attr_name,
                        const char* value, size_t length) {
  tensorflow::NameAttrList func_name;
  func_name.set_name(string(value, value + length));
  desc->node_builder.Attr(attr_name, func_name);
}

void TF_SetAttrShape(TF_OperationDescription* desc, const char* attr_name,
                     const int64_t* dims, int num_dims) {

        "Encountered while processing input ", i, " into function '", fn_name,
        "'");
    TF_RETURN_WITH_CONTEXT_IF_ERROR(ValidateNonRefOutput(node, idx),
                                    "Encountered while processing input ", i,
                                    " into function '", fn_name, "'");

    input_tensors->emplace_back(node, idx);

    const auto& iter = input_nodes->find(node);

UserInDB(
    username="john",
    password="secret",
    email="******@****.***",
    full_name=None,
)
```

或更精准，直接把可能会用到的内容与 `user_dict` 一起使用：

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

#### 用其它模型中的内容生成 Pydantic 模型

UserInDB(
    username="john",
    password="secret",
    email="******@****.***",
    full_name=None,
)
```

⚖️ 🌅 ⚫️❔, ⚙️ `user_dict` 🔗, ⏮️ ⚫️❔ 🎚 ⚫️ 💪 ✔️ 🔮:

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

#### Pydantic 🏷 ⚪️➡️ 🎚 ➕1️⃣

    password="secret",
    email="******@****.***",
    full_name=None,
)
```

Or more exactly, using `user_dict` directly, with whatever contents it might have in the future:

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

    email="******@****.***",
    full_name=None,
)
```

Или, если для большей точности мы напрямую используем `user_dict` с любым потенциальным содержимым, то этот пример будет выглядеть так:

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

    password="secret",
    email="******@****.***",
    full_name=None,
)
```

Ou mais exatamente, usando `user_dict` diretamente, com qualquer conteúdo que ele possa ter no futuro:

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

    password="secret",
    email="******@****.***",
    full_name=None,
)
```

Oder, präziser, `user_dict` wird direkt verwendet, welche Werte es auch immer haben mag:

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```